A recent article on Environmental Leader argues the PET is environmentally superior to glass or aluminum as a food/beverage packaging material. Our recent work confirms that PET has significantly lower life-cycle GHG emissions compared to glass or virgin aluminum. For a typical 12 oz container, here are some sample GHG emissions figures based on materials and fabrication (assuming container weights of 365 g for glass, 54 g for PET, 40 g for aluminum):

Glass (virgin): 256 g of CO2-e

Glass (80% recycled content): 217 g of CO2-eq

PET (virgin): 139 g of CO2-eq

Aluminum (virgin): 521 g of CO2-eq

Aluminum (100% recycled content): 37 g of CO2-eq

So, unless the aluminum includes mostly recycled content, PET would be the best choice from a carbon footprint perspective. When transportation is factored in, glass becomes even less attractive because of its weight. Both aluminum and glass production require very high temperatures and are therefore very energy intensive.

August 14, 2008

On my current visit to India, I've been looking at everything through my "sustainability lens". I am not sure if India is really representative of most big emerging economies, but my guess is that it is not very different from China when it comes to sustainability.

The first thing that strikes an observer is that green labels and practices -- such as organic, local, reduced packaging, recycling, low emissions, low carbon footprint, renewable energy, etc. -- are largely absent from public discussion. There are occasional newspaper articles, but both consumers and corporations are focused on other things: quality, cost, convenience. This is not very different from the state of affairs in Western countries just a decade ago. Given the huge numbers of people that are just short of becoming big consumers in India -- and the money to be made by selling to them -- my best guess is that sustainability is unlikely to be front and center in public consciousness for quite a long time.

Government is not leading the way with policy initiatives, so it all comes down to motivating the private sector to take the lead. I believe that any immediate sustainability solutions for India (and possibly China as well) would need to include cost-reduction and profit-making at the core, relying more on the market and less on subsidies, tax breaks and the like. The low cost of labor in these parts might be a big advantage in implementing these solutions. Just looking around, some possibilities come to mind immediately:

Biodiesel production from used vegetable oils, animal fats and non-edible oil seeds, without consuming edible foods or converting agricultural production. Given the soaring demand for diesel in India and increasing prices (one of the reasons is the increasing use of private diesel generators to offset power outages), an alternative fuel from waste products might be profitable while reducing net GHG emissions. There are some biodiesel plants in operation in India, but the fuel is not widely known or used at this point.

Small-scale, solar energy systems that can be installed on roofs, possibly off-grid initially. Given the frequent power outages in India and the big part of the population that still doesn't have electricity, something like this is overdue. The cost of solar cells is still an obstacle, but the economics may start making sense in a few years as the $1/watt barrier is breached on a large scale. Government subsidies may be needed to offset capital costs for consumers/businesses, but may turn out to be cheaper than building expensive new coal/gas/nuclear plants -- not to mention lower life-cycle GHG emissions.

August 04, 2008

How does the location of production influence a product's carbon footprint? Transport to the consumption location is certainly one factor, but what is often overlooked is that the production emissions may vary depending on where it is done.

If the finished product (or the components/ingredients used in production) must be air-freighted, then it is a good bet that air transport distances will heavily influence the final carbon footprint -- this is particularly true for air-freighted food products, where transport emissions can far exceed production emissions. On the other hand, rail and ocean transport are quite benign from a carbon perspective, even with refrigeration added. Road transport can be a critical factor if the production emissions are relatively small -- as in the case of many fruits, vegetables and grains. In one analysis we did concerning transporting dry food ingredients (such as dry beans or grains) from China and the US mid-west to the US west coast, the Chinese imports had the lower carbon emissions. For ocean transport from China to the US, the critical transport links are actually the road segments on either end, and not the long ocean segment that first comes to mind.

If older technology is used in overseas production, for example, then the production emissions per unit product can easily be higher overseas. Even if the same state-of-the-art technology is used at the overseas location, the actual emissions will depend on the fuels and electricity sources used. Here are average CO2 emission factors for energy production in selected countries (2005 data from IEA):

A related note: Textile and apparel production in China is exacting a heavy environmental toll there. Chinese companies reportedly dump untreated waste water into lakes and rivers. Proper wastewater treatment will add to the product's carbon footprint (US average: 742 Kg of CO2-eq/million gallons of wastewater treated). Prices in the US may be artificially low because we are not paying the costs of pollution for imported products. A VP at Liz Claiborne says the environment is the new frontier after labor issues in overseas production.

August 03, 2008

Global supply chains are under increasing pressure from rising transportation costs. A report in today's New York Times cites examples of companies moving some production closer to consumers: Ikea recently opened its first US factory and furniture manufacture is starting to return to the US; some electronics companies are returning to Mexico (from China) to be closer to the US market; China's steel exports to the US are dropping by 20% a year, while US steel manufacture has been rising after years of decline.

The report talks about the possibility of the "neighborhood effect" and a regionalized trading world. In such a trade regime, China would buy its raw materials such as iron ore from Australia rather than Brazil and farm out more of its manufacturing to nearby Asian locations. Similarly, Mexico's assembly plants near the US border would become more important for the US market. Out-of-season fruits and vegetables transported over long distances may turn into luxury items.

This is exactly along the lines of what we learned from our simulation study of global trade under distance constraints, conducted in 2006. We used an agent-based simulation model to explore the possible consequences of increased fuel costs and/or tigher greenhouse gas emissions constraints in an artificial global economy. The simulations showed interesting network structures developing between traders and a strong tendency for most trade to occur within local regions. Our simulations also showed that diversified local economies would adapt better to distance constraints than scenarios where each region specializes in a small number of goods.

Carbon footprints of food products – or carbon foodprints – are increasingly a topic of discussion. We regularly receive questions and requests related to life-cycle carbon footprint analysis of various food products. Having worked on a few such projects – ranging from consulting work to software/database development – I’ll share some thoughts and observations on carbon foodprints.

A common method of compiling a large carbon foodprint data set is to scour the LCA (life-cycle assessment) literature or energy analysis literature for results that could be used directly or with some modest additional computation. For example, in some of our projects, we’ve used LCA results from Europe as a proxy for US results (because of a lack of US-specific results for many food commodities), and modified the results to reflect some US conditions such as transport distances, GHG emissions from electricity generation, etc. This is sometimes the only available option, but it is fraught with difficulties and uncertainties.

Most published life-cycle energy or emissions results are specific to a particular geographical region and time period. These results typically depend on a range of variables such as local climate, soil type and condition, irrigation requirements, specific production methods used (such as conventional, organic or greenhouse crops; soil tilling practices; grain-fed or free-range animals; wild or farmed seafood; etc.), energy sources used, current state of technology, and so on. These details change from place to place, and some of the details also change over time. Moreover, each study may include specific assumptions and boundaries that vary from other studies. Taking results generated for one set of conditions and using them for a completely different place and time, and especially making foodprint comparisons between different products, is risky business – we just don’t know the magnitude of the errors involved in this approach.

An alternative approach is to look for underlying agricultural input data instead of LCA results – such as fertilizers, pesticides, water, fuel, electricity and other inputs used to produce an agricultural product – and then do a clean, streamlined LCA that is consistent across different products. This obviously works much better, but it is not that easy to find raw agricultural data specific to each product. Moreover, the agricultural data would have to be specific to the region of interest in order to overcome some of the objections raised earlier. In a large country like the US, the data may have to be specific to each major agricultural region.

Using exactly this type of regional agricultural input data, here is a comparison of two types of tomatoes grown in California. Taking into account most purchased inputs that are consumed (except pesticides and some minor inputs due to lack of data), and excluding machinery and labor for now, a quick streamlined LCA up to the output of the farms shows that one type of tomato has double the carbon foodprint of the other:

Fresh market tomatoes grown in the San Joaquin Valley: 0.157 Kg of CO2-eq/Kg of product

Processing tomatoes grown in the Sacramento Valley: 0.079 Kg of CO2-eq/Kg of product

The absolute values are small here, but such differences could matter if the results are going to be used to decide the lowest-impact location to source a product (taking into account transport, etc.). If the purpose is to compare tomatoes (or vegetables in general) with meat products, then an average of all tomatoes or all vegetables may be sufficient, as long as there are no order-of-magnitude differences among tomatoes/vegetables.

The required degree of accuracy will depend on the application. For a 30,000 foot view of carbon foodprints, we only need the correct orders of magnitude, and this doesn’t require a lot of effort. But if a business is making procurement decisions on the basis of carbon foodprints, or developing detailed carbon eco-labels for consumers to use, then more accurate results – which may require locational and temporal specificity – would be necessary. So, the next time you see carbon foodprint values published anywhere, you may want to ask how they got the numbers. The methodology selected, and the effort put into generating the results, should match the application.